1. Field of the Invention
The present invention relates to an image reduction method for processing a binary image, an image processing device and a method of controlling the image processing device.
2. Description of the Related Art
In general, a simple thinning-out method is used as a related-art method of reducing a binary image. According to the simple thinning-out method, a pixel is eliminated from an image at each fixed interval in accordance with a reduction rate, and a reduced image is expressed with remaining pixels. For example, in a case in which image data is reduced by 50%, or its reduction rate is 50%, a reduced image is obtained by eliminating every other pixel.
However, according to this simple thinning-out method, a thin line or the like expressed by one dot is eliminated entirely from a reduced image in a case in which the thin line or the like corresponds to pixels to be eliminated. The above situation is called line breaking or dot missing. Thus, a weak point of the simple thinning-out method is that a degree of decrease in quality of the reduced image is large.
For instance, an image reduction method carrying out an OR process is used as a method of reducing the decrease in quality of the reduced image. The image reduction method carrying out the OR process is a method that uses a result of carrying out a logical OR process to two dots when composing a single dot from the two dots during an image reduction process. This image reduction method carrying out the OR process, unlike the above-described simple thinning-out method, prevents elimination of a line in a reduced image. At the same time, the image reduction method carrying out the OR process occasionally causes a failure in which a part to be remained as white becomes black in the reduced image. In other words, line thickening or blackening occasionally occurs in the reduced image.
A method dealing with a problem about the decrease in quality of the reduced image caused by the above-described image reduction methods is a conditional OR process, for example. According to the conditional OR process, values of pixel data after an image reduction process are determined by the following equation (I).R(n)=((NOT(R(n−1)))AND(B(n)))OR(B(n−1))  (I)
R(n), R(n−1), B(n) and B(n−1) in the above equation (I) indicate pixel data after an image reduction process, previously-reduced image data, currently focused pixel data, and pixel data that is one pixel before the currently focused pixel data, respectively. A positioning relation between the pixel data of original image data and the pixel data of image data after being processed through the image reduction process is shown in FIGS. 1A and 1B.
By adopting the conditional OR process to the image reduction process, white pixels can remain in a reduced image, even in a case in which the white pixels are arranged so that the white pixels become black by the simple thinning-out method. Thus, the adoption of the conditional OR process to the image reduction process can suppress decrease in quality of a reduced image.
The above-described conditional OR process is basically a process to reduce two pixels to one as shown in FIGS. 1A and 1B, and, thus, needs to store a resulted pixel that is necessary for the next calculation, separately for each focused pixel whose order is an odd or even number, as shown in FIGS. 2A, 2B and 2C.
In other words, a result of carrying out the conditional OR process to focused pixels whose orders are odd numbers and a result of carrying out the conditional OR process to focused pixels whose orders are even numbers are different information series. Thus, a result of carrying out the conditional OR process must be stored for processing each of the focused pixels whose orders are odd numbers and the focused pixels whose orders are even numbers.
In a case in which this conditional OR process is applied to an image reduction process in a sub-scanning direction, white pixels can remain in a reduced image similarly to an image reduction process in a main-scanning direction, even if white pixels are arranged so that the white pixels become black by the simple thinning-out method. Thus, the adoption of the conditional OR process to the image reduction process can suppress decrease in quality of a reduced image.
However, in the case in which the conditional OR process is applied to the image reduction in the sub-scanning direction, memory means is necessary for storing results of carrying out the conditional OR process to each of a line whose order is an odd number and a line whose order is an even number, thereby increasing a device cost.